Event related brain potential (ERP) waveforms consist of several components extending in time, frequency and topographical space. Therefore, an efficient processing of data which involves the time, frequency and space features of the signal, may facilitate to understand the plausible connections among the functions, the anatomical structures and neurophysiological mechanisms of the brain. Wavelet transform (WT) is a powerful signal processing tool for extracting the ERP components occuring at different time and frequency spots. Using the frequency selectivities and spatial features of the event-related EEG changes, it is also possible to identify event-related potentials in single trials that are not time- or phase-locked to the event. Our previous studies since 1993 show that WT can be very useful in both identifying the subcomponents of averaged ERPs that are more specifically related to distinct subprocesses of the main cognitive operation in an ERP paradigm and in the detection of main event related signal features in single trials. Based on this experience, we developed a software with a graphical user interface, that can handle original data files from various ERP equipment suppliers and standard data file formats such as EDF in both continuous and epoched forms using conventional analysis techniques and WT based temporal and spatial decomposition tools. The facilities of the software will be presented using both previously published data on normative groups and on recent clinical data obtained from patients with Alzheimer’s disease and Schizophrenia.